Evaluating ChatGPT-4's Diagnostic Accuracy: Impact of Visual Data Integration.

BACKGROUND: In the evolving field of health care, multimodal generative artificial intelligence (AI) systems, such as ChatGPT-4 with vision (ChatGPT-4V), represent a significant advancement, as they integrate visual data with text data. This integration has the potential to revolutionize clinical diagnostics by offering more comprehensive analysis capabilities. However, the impact on diagnostic accuracy of using image data to augment ChatGPT-4 remains unclear. OBJECTIVE: This study aims to assess the impact of adding image data on ChatGPT-4's diagnostic accuracy and provide insights into how image data integration can enhance the accuracy of multimodal AI in medical diagnostics. Specifically, this study endeavored to compare the diagnostic accuracy between ChatGPT-4V, which processed both text and image data, and its counterpart, ChatGPT-4, which only uses text data. METHODS: We identified a total of 557 case reports published in the American Journal of Case Reports from January 2022 to March 2023. After excluding cases that were nondiagnostic, pediatric, and lacking image data, we included 363 case descriptions with their final diagnoses and associated images. We compared the diagnostic accuracy of ChatGPT-4V and ChatGPT-4 without vision based on their ability to include the final diagnoses within differential diagnosis lists. Two independent physicians evaluated their accuracy, with a third resolving any discrepancies, ensuring a rigorous and objective analysis. RESULTS: The integration of image data into ChatGPT-4V did not significantly enhance diagnostic accuracy, showing that final diagnoses were included in the top 10 differential diagnosis lists at a rate of 85.1% (n=309), comparable to the rate of 87.9% (n=319) for the text-only version (P=.33). Notably, ChatGPT-4V's performance in correctly identifying the top diagnosis was inferior, at 44.4% (n=161), compared with 55.9% (n=203) for the text-only version (P=.002, χ2 test). Additionally, ChatGPT-4's self-reports showed that image data accounted for 30% of the weight in developing the differential diagnosis lists in more than half of cases. CONCLUSIONS: Our findings reveal that currently, ChatGPT-4V predominantly relies on textual data, limiting its ability to fully use the diagnostic potential of visual information. This study underscores the need for further development of multimodal generative AI systems to effectively integrate and use clinical image data. Enhancing the diagnostic performance of such AI systems through improved multimodal data integration could significantly benefit patient care by providing more accurate and comprehensive diagnostic insights. Future research should focus on overcoming these limitations, paving the way for the practical application of advanced AI in medicine.

Occult endocrine disorders newly diagnosed in patients with post-COVID-19 symptoms.

Determination of long COVID requires ruling out alternative diagnoses, but there has been no report on the features of alternative diagnoses. This study was a single-center retrospective study of outpatients who visited our clinic between February 2021 and June 2023 that was carried out to determine the characteristics of alternative diagnoses in patients with post-COVID-19 symptoms. In a total of 731 patients, 50 patients (6.8%) were newly diagnosed with 52 diseases requiring medical intervention, and 16 (32%) of those 50 patients (2.2% of the total) were considered to have priority for treatment of the newly diagnosed disorders over long COVID treatment. The proportion of patients with a new diagnosis increased with advance of age, with 15.7% of the patients aged 60 years or older having a new diagnosis. Endocrine and metabolic diseases and hematological and respiratory diseases were the most common, being detected in eight patients (16%) each. Although 35 of the 52 diseases (67%) were related to their symptoms, endocrine and metabolic diseases were the least associated with specific symptoms. Other disorders that require attention were found especially in elderly patients with symptomatic long COVID. Thus, appropriate assessment and differentiation from alternative diagnoses are necessary for managing long COVID.

Characteristics of Functional Hyperthermia Detected in an Outpatient Clinic for Fever of Unknown Origin.

Background: Functional hyperthermia (FH) is characterized by hyperthermia resulting from sympathetic hyperactivity rather than inflammation, and it is frequently overlooked by medical practitioners due to the absence of abnormalities in a medical examination. Although FH is an important differential diagnosis for fever of unknown origin (FUO), the literature on FUO cases in Japan lacks information on FH. In this study, we aimed to uncover the population of FH patients hidden in FUO cases. Methods: An outpatient clinic for FUO was established at Okayama University Hospital, and 132 patients were examined during the period from May 2019 to February 2022. Results: A diagnosis of FH was made in 31.1% of the FUO cases, and FH predominantly affected individuals in their third and fourth decades of life with a higher incidence in females (68.3%). The frequency of a history of psychiatric illness was higher in patients with FH than in patients with other febrile illnesses. Although the C-reactive protein (CRP) is generally negative in FH cases, some obese patients, with a body mass index ≥ 25 had slightly elevated levels of CRP but were diagnosed with FH. Conclusions: The results showed the importance of identifying FH when encountering patients with FUO without any organic etiology.

Clinical decision support system using a machine learning model to assist simultaneous cardiopulmonary auscultation: Open-label randomized controlled trial.

Background: The utility of a clinical decision support system using a machine learning (ML) model for simultaneous cardiac and pulmonary auscultation is unknown. Objective: This study aimed to develop and evaluate an ML system's utility for cardiopulmonary auscultation. Methods: First, we developed an ML system for cardiopulmonary auscultation, using cardiopulmonary sound files from our previous study. The technique involved pre-processing, feature extraction, and classification through several neural network layers. After integration, the output class was categorized as "normal," "abnormal," or "undetermined." Second, we evaluated the ML system with 24 junior residents in an open-label randomized controlled trial at a university hospital. Participants were randomly assigned to the ML system group (intervention) or conventional auscultation group (control). During training, participants listened to four cardiac and four pulmonary sounds, all of which were correctly classified. Then, participants classified a series of 16 simultaneous cardiopulmonary sounds. The control group auscultated the sounds using noise-cancelling headphones, while the intervention group did so by watching recommendations from the ML system. Results: The total scores for correctly identified normal or abnormal cardiopulmonary sounds in the intervention group were significantly higher than those in the control group (366/384 [95.3%] vs. 343/384 [89.3%], P = 0.003). The cardiac test score in the intervention group was better (111/192 [57.8%] vs. 90/192 [46.9%], P = 0.04); there was no significant difference in pulmonary auscultation. Conclusions: The ML-based system improved the accuracy of cardiopulmonary auscultation for junior residents. This result suggests that the system can assist early-career physicians in accurate screening.

Clinical characteristics of female long COVID patients with menstrual symptoms: a retrospective study from a Japanese outpatient clinic.

PURPOSE: To elucidate the impact of long COVID on menstruation and mental health, medical records of patients with long COVID were evaluated. METHODS: Symptoms of long COVID, QOL, mental health, and related endocrine data were compared between two groups with and without menstrual disturbances. RESULTS: Of 349 female patients who visited our clinic between February 2021 and March 2023, 223 patients with long COVID (aged 18-50 years) were included. Forty-four (19.7%) of the patients had menstrual symptoms associated with long COVID. The patients with menstrual symptoms were older than those without menstrual symptoms (42.5 vs. 38 years). The percentage of patients with menstrual symptoms was higher during the Omicron phase (24%) than during the Preceding (13%) and Delta (12%) phases. Cycle irregularity was the most frequent (in 63.6% of the patients), followed by severe pain (25%), heavy bleeding (20.5%), perimenopausal symptoms (18.2%), and premenstrual syndrome (15.9%). Fatigue and depression were the most frequent complications. Scores for fatigue and for QOL were significantly worse in long COVID patients with menstrual symptoms. Results of endocrine examinations showed significantly increased cortisol levels in patients with menstrual complaints. CONCLUSION: Long COVID has an impact on menstrual conditions and on QOL related to menstrual conditions.

Relevance of complement immunity with brain fog in patients with long COVID.

INTRODUCTION: This study aimed to elucidate the prevalence and clinical characteristics of patients with long COVID (coronavirus disease 2019), especially focusing on 50% hemolytic complement activity (CH50). METHODS: This retrospective observational study focused on patients who visited Okayama University Hospital (Japan) for the treatment of long COVID between February 2021 and March 2023. CH50 levels were measured using liposome immunometric assay (Autokit CH50 Assay, FUJIFILM Wako Pure Chemical Corporation, Japan); high CH50 was defined as ≥59 U/mL. Univariate analyses assessed differences in the clinical background, long COVID symptoms, inflammatory markers, and clinical scores of patients with normal and high CH50. Logistic regression model investigated the association between high CH50 levels and these factors. RESULTS: Of 659 patients who visited our hospital, 478 patients were included. Of these, 284 (59.4%) patients had high CH50 levels. Poor concentration was significantly more frequent in the high CH50 group (7.2% vs. 13.7%), whereas no differences were observed in other subjective symptoms (fatigue, headache, insomnia, dyspnea, tiredness, and brain fog). Multivariate analysis was performed on factors that could be associated with poor concentration, suggesting a significant relationship to high CH50 levels (adjusted odds ratio [aOR], 2.70; 95% confidence interval [CI], 1.33-5.49). Also, high CH50 was significantly associated with brain fog (aOR, 1.66; 95% CI, 1.04-2.66). CONCLUSIONS: High CH50 levels were frequently reported in individuals with long COVID, indicating a relationship with brain fog. Future in-depth research should examine the pathological role and causal link between complement immunity and the development of long COVID.

[Report: Symposium "Fostering the Power to Open Up the Future and Collaboration among Academic Societies in the Field of Social Medicine: How to Promote and Support the Activities of Young Scientists"].

The recruitment and training of early-career researchers are important for the development of science, especially in countries with low birth rates, such as Japan. In several academic societies for social medicine, early-career researchers have formed associations for the purposes of networking and career development. However, to date, little information about the activities of these associations has been shared. Therefore, we organized a symposium at the 93rd Annual Meeting of the Japanese Society for Hygiene (March 4, 2023) to introduce the early-career researcher associations that have been formed within five academic societies namely the Japanese Society for Hygiene, Japan Epidemiological Association, Japan Society for Occupational Health, Japan Society for Medical Education, and Japan Society for Healthcare Administration. In this paper, we summarize the activities, challenges, and future prospects of each association and their strategies for future development and collaboration on the basis of presentations and discussions at the symposium.

Characteristics of Persistent Symptoms Manifested after SARS-CoV-2 Vaccination: An Observational Retrospective Study in a Specialized Clinic for Vaccination-Related Adverse Events.

Background: Although many adverse reactions after SARS-CoV-2 vaccination have been reported, there have been few comprehensive studies on persistent symptoms after SARS-CoV-2 vaccination. The aim of this study was to determine the clinical characteristics of patients with various persistent symptoms after SARS-CoV-2 vaccination. Methods: A retrospective descriptive study was performed for patients who visited a specialized clinic established at Okayama University Hospital to evaluate adverse events after SARS-CoV-2 vaccination during the period from April 2021 to March 2023. Results: Descriptive analysis was performed for 121 of 127 patients who visited the clinic during the study period, and separate analysis was performed for the other 6 patients who had serious complications, who required treatment with prednisolone, and who had persistent symptoms. The median [interquartile range] age of the patients was 48 years [31-64 years], and the patients included 44 males (36.4%) and 77 females (63.6%). The most frequent symptoms were sensory impairment (34 patients, 28.1%), general fatigue (30 patients, 24.8%), fever/low-grade fever (21 patients, 17.4%), and headache (21 patients, 17.4%). Serious complications included myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), sarcoidosis, aseptic meningitis, neuromyelitis optica spectrum disorders (NMOSDs), tendon adhesions, and idiopathic thrombocytopenia. Conclusions: Although causal relationships were not determined, 15 persistent symptoms after SARS-CoV-2 vaccination were characterized. All of the symptoms had onset from 12 hours to one week after vaccination, with 10 symptoms persisting for 6 months or longer. The most frequent symptom was sensory impairment.

ChatGPT-Generated Differential Diagnosis Lists for Complex Case-Derived Clinical Vignettes: Diagnostic Accuracy Evaluation.

BACKGROUND: The diagnostic accuracy of differential diagnoses generated by artificial intelligence chatbots, including ChatGPT models, for complex clinical vignettes derived from general internal medicine (GIM) department case reports is unknown. OBJECTIVE: This study aims to evaluate the accuracy of the differential diagnosis lists generated by both third-generation ChatGPT (ChatGPT-3.5) and fourth-generation ChatGPT (ChatGPT-4) by using case vignettes from case reports published by the Department of GIM of Dokkyo Medical University Hospital, Japan. METHODS: We searched PubMed for case reports. Upon identification, physicians selected diagnostic cases, determined the final diagnosis, and displayed them into clinical vignettes. Physicians typed the determined text with the clinical vignettes in the ChatGPT-3.5 and ChatGPT-4 prompts to generate the top 10 differential diagnoses. The ChatGPT models were not specially trained or further reinforced for this task. Three GIM physicians from other medical institutions created differential diagnosis lists by reading the same clinical vignettes. We measured the rate of correct diagnosis within the top 10 differential diagnosis lists, top 5 differential diagnosis lists, and the top diagnosis. RESULTS: In total, 52 case reports were analyzed. The rates of correct diagnosis by ChatGPT-4 within the top 10 differential diagnosis lists, top 5 differential diagnosis lists, and top diagnosis were 83% (43/52), 81% (42/52), and 60% (31/52), respectively. The rates of correct diagnosis by ChatGPT-3.5 within the top 10 differential diagnosis lists, top 5 differential diagnosis lists, and top diagnosis were 73% (38/52), 65% (34/52), and 42% (22/52), respectively. The rates of correct diagnosis by ChatGPT-4 were comparable to those by physicians within the top 10 (43/52, 83% vs 39/52, 75%, respectively; P=.47) and within the top 5 (42/52, 81% vs 35/52, 67%, respectively; P=.18) differential diagnosis lists and top diagnosis (31/52, 60% vs 26/52, 50%, respectively; P=.43) although the difference was not significant. The ChatGPT models' diagnostic accuracy did not significantly vary based on open access status or the publication date (before 2011 vs 2022). CONCLUSIONS: This study demonstrates the potential diagnostic accuracy of differential diagnosis lists generated using ChatGPT-3.5 and ChatGPT-4 for complex clinical vignettes from case reports published by the GIM department. The rate of correct diagnoses within the top 10 and top 5 differential diagnosis lists generated by ChatGPT-4 exceeds 80%. Although derived from a limited data set of case reports from a single department, our findings highlight the potential utility of ChatGPT-4 as a supplementary tool for physicians, particularly for those affiliated with the GIM department. Further investigations should explore the diagnostic accuracy of ChatGPT by using distinct case materials beyond its training data. Such efforts will provide a comprehensive insight into the role of artificial intelligence in enhancing clinical decision-making.

Acute arthritis caused by sarcoidosis.

Here we report a case of sarcoidosis which demonstrated with bilateral ankle arthritis. We usually do not consider sarcoidosis routinely for the differential diagnosis of acute arthritis, however, up to 15 to 25% of sarcoidosis complicate arthritis, typically in ankle joints. Sarcoid arthritis is reported to occur mainly in young northern Europe women, whereas this case intimate that we should take sarcoidosis into account as the differential diagnosis of ankle arthralgia also among Asian men especially when combining upper respiratory symptoms.

Utility of Serum Ferritin for Predicting Myalgic Encephalomyelitis/Chronic Fatigue Syndrome in Patients with Long COVID.

OBJECTIVE: The most common symptom of post-acute coronavirus disease 2019 (COVID-19) is fatigue, and it potentially leads to myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS); however, a specific prognosticator is lacking. We aimed to elucidate the clinical characteristics of patients who developed ME/CFS after COVID-19. METHODS: In this retrospective observational study, patients who visited Okayama University Hospital for long COVID between February 2021 and March 2022 were investigated. RESULTS: Of the 234 patients, 139 (59.4%) had fatigue symptoms. Fifty patients with fatigue symptoms (21.4%) met the criteria for ME/CFS (ME/CFS group), while the other 89 patients did not (non-ME/CFS group); 95 patients had no fatigue complaints (no-fatigue group). Although the patients' backgrounds were not significantly different between the three groups, the ME/CFS group presented the highest scores on the self-rating symptom scales, including the Fatigue Assessment Scale (FAS), EuroQol, and the Self-Rating Depression Scale (SDS). Furthermore, serum ferritin levels, which were correlated with FAS and SDS scores, were significantly higher in the ME/CFS group (193.0 µg/L, interquartile range (IQR): 58.8-353.8) than in the non-ME/CFS group (98.2 µg/L, 40.4-251.5) and no-fatigue group (86.7 µg/L, 37.5-209.0), and a high serum ferritin level was prominent in female patients. Endocrine workup further showed that the ME/CFS group had higher thyrotropin levels but lower growth hormone levels in serum and that insulin-like growth factor-I levels were inversely correlated with ferritin levels (R = -0.328, p < 0.05). CONCLUSIONS: Serum ferritin level is a possible predictor of the development of ME/CFS related to long COVID, especially in female patients.

Manifestation of Headache Affecting Quality of Life in Long COVID Patients.

Objectives: The present study aimed to elucidate the characteristics of long COVID patients with headaches. Methods: A single-center retrospective observational study was performed for long COVID outpatients who visited our hospital from 12 February 2021 to 30 November 2022. Results: A total of 482 long COVID patients, after excluding 6, were divided into two groups: the Headache group of patients with complaints of headache (113 patients: 23.4%) and the remaining Headache-free group. Patients in the Headache group were younger (median age: 37 years) than patients in the Headache-free group (42 years), while the ratio of females (56%) in the Headache group was nearly the same as that in the Headache-free group (54%). The proportion of patients in the Headache group who were infected in the Omicron-dominant phase (61%) was larger than the proportions of patients infected in the Delta (24%) and preceding (15%) phases, and that trend was significantly different from the trend in the Headache-free group. The duration before the first visit for long COVID was shorter in the Headache group (71 days) than in the Headache-free group (84 days). The proportions of patients in the Headache group with comorbid symptoms, including general fatigue (76.1%), insomnia (36.3%), dizziness (16.8%), fever (9.7%), and chest pain (5.3%) were larger than the proportions of patients in the Headache-free group, whereas blood biochemical data were not significantly different between the two groups. Interestingly, patients in the Headache group had significant deteriorations of scores indicating depression and scores for quality of life and general fatigue. In multivariate analysis, headache, insomnia, dizziness, lethargy, and numbness were shown to be involved in the quality of life (QOL) of long COVID patients. Conclusions: The manifestation of headaches related to long COVID was found to have a significant impact on social and psychological activities. Alleviation of headaches should be a priority for the effective treatment of long COVID.

Symptomatic Characteristics of Hypozincemia Detected in Long COVID Patients.

OBJECTIVES: The aim of this study was to determine the characteristics of hypozincemia in long COVID patients. METHODS: This study was a single-center retrospective observational study for outpatients who visited the long COVID clinic established in a university hospital during the period from 15 February 2021 to 28 February 2022. Characteristics of patients with a serum zinc concentration lower than 70 µg/dL (10.7 µmol/L) were compared with characteristics of patients with normozincemia. RESULTS: In a total of 194 patients with long COVID after excluding 32 patients, hypozincemia was detected in 43 patients (22.2%) including 16 male patients (37.2%) and 27 female patients (62.8%). Among various parameters including the background characteristics of the patients and medical histories, the patients with hypozincemia were significantly older than the patients with normozincemia (median age: 50 vs. 39 years). A significant negative correlation was found between serum zinc concentrations and age in male patients (R = -0.39; p < 0.01) but not in female patients. In addition, there was no significant correlation between serum zinc levels and inflammatory markers. General fatigue was the most frequent symptom in both male patients with hypozincemia (9 out of 16: 56.3%) and female patients with hypozincemia (8 out of 27: 29.6%). Patients with severe hypozincemia (serum zinc level lower than 60 µg/dL) had major complaints of dysosmia and dysgeusia, which were more frequent complaints than general fatigue. CONCLUSIONS: The most frequent symptom in long COVID patients with hypozincemia was general fatigue. Serum zinc levels should be measured in long COVID patients with general fatigue, particularly in male patients.

Trends in Long COVID Symptoms in Japanese Teenage Patients.

Background: Since the start of the global pandemic of coronavirus disease 2019 (COVID-19), not only adults but also many children have suffered from it. However, the clinical characteristics of long COVID in children remain unclear. Methods: In this retrospective observational study conducted in a single facility, we reviewed the medical records of all long COVID patients who visited Okayama University Hospital from February 2021 to October 2022, and we compared the clinical characteristics of long COVID in teenagers (11 to 18 years of age) with those in adults. Results: Data for 452 long COVID patients including 54 teenagers (11.9%) were analyzed. Fatigue was the most frequent symptom in teenagers (55.6% of the patients) and also in adults. On the other hand, the percentage of teenagers who complained of headache, which was the second most frequent complaint, was significantly higher than the percentage of adults (35.2% vs. 21.9%, p < 0.05). A comparison of the frequencies of symptoms depending on the viral variant showed that fatigue and headache were predominant symptoms in the Omicron variant phase. Of the 50 teenagers who were enrolled in schools, 28 (56.0%) could not attend school due to long COVID symptoms. The most common symptoms as reasons for absence from school were fatigue (85.7% of the patients), headache (42.9%), and insomnia (32.1%). Conclusions: Attention should be paid to the symptoms of fatigue and headache in teenagers with long COVID.

Differences in Stress Perception of Medical Students Depending on In-Person Communication and Online Communication during the COVID-19 Pandemic: A Japanese Cross-Sectional Survey.

BACKGROUND: Excessive psychological stress in medical students affects their mental health and causes problems such as burnout and depression. Furthermore, changes in the learning environment to online learning due to the COVID-19 pandemic have had a psychological effect on medical students. However, the relationships between medical students' perceived stress and different methods of communication, including in-person and online communication, remain unclear. The purpose of this study was to investigate the differences in stress perception of medical students depending on in-person communication and online communication during the COVID-19 pandemic. METHODS: This study was a cross-sectional study conducted from September to October in 2020. All of the students of Okayama University School of Medicine were asked to participate in a questionnaire survey. The explanatory variables were the frequency and length of communications with others (by in-person or online communication), empathy, and lifestyle. The main outcome measure was perceived stress. Subgroup analysis was conducted for students who preferred to be by themselves and students who preferred to study together and interact with other people. Univariate analysis and multivariate multiple regression analysis were conducted. Gender and grade, which have been shown to be associated with stress in previous studies, were used as covariates for multiple regression analysis. RESULTS: Valid responses to the questionnaire survey were received from 211 (29.4%) of the 717 students. There was no significant association between perceived stress and online communication, but the number of people with which students had in-person communication (1-2 people compared to 0 as a control, regression coefficient [B] = -4.4, 95% confidence interval [CI]; -7.8, -1.1, more than 10 people, B = -12, 95% CI: -18, -5.8) and the length of communication (more than 120 min, B = -4.5, 95% CI: -8.1, -0.92) were associated with a reduction in perceived stress. In subgroup analysis, the number of people with in-person communication and the length of communication had significant associations with stress reduction even in the group of students who had a preference for being by themselves. CONCLUSION: In-person communications rather than online communications were associated with a lower level of perceived stress. In subgroup analysis, this trend was statistically significant in the group of students who had a preference for being by themselves.

Characteristics of Sleep Disturbance in Patients with Long COVID: A Retrospective Observational Study in Japan.

OBJECTIVES: The objective of this study was to determine the clinical and endocrinological features of sleep disturbance in patients with long COVID. METHODS: This study was a single-center retrospective observational study for patients who visited the COVID-19 aftercare outpatient clinic (CAC) established in Okayama University Hospital in Japan during the period from 15 February 2021 to 29 July 2022. The long COVID patients were divided into two groups based on the presence or absence of sleep disturbance, and the clinical and laboratory characteristics of the patients were analyzed. RESULTS: Out of 363 patients with long COVID, after excluding 6 patients, 60 patients (16.5%) (55% males, median age of 38 years) complaining of sleep disturbance were compared with 303 patients (83.5%) (43% males, median age of 40 years) without sleep-related symptoms. Although there were no significant differences in clinical backgrounds and severities of COVID-19 between the two groups by the multivariate analysis, the percentage of long COVID patients with sleep disturbance was significantly increased among patients infected in the Omicron-dominant phase. In addition, the prevalence rate of sleep disturbance in patients when infected in the Omicron phase (24.8%) was two-times higher than that in patients infected in the Delta phase (12.8%). Of note, the percentages of patients with sleep disturbance who also complained of general fatigue, headache, concentration loss, anxiety, low-grade fever, and brain fog symptoms were higher than the percentages of patients without sleep disturbance who had the same complaints. Among the types of sleep disturbance, the percentage of patients who complained of loss of sleep induction (75%) was much higher than the percentage of patients with early-awakening sleep disturbance (6.7%), and many of the patients with mid-awakening types of insomnia had brain fog symptoms. Endocrine examinations revealed that long COVID patients with sleep disturbance had significantly higher levels of plasma adrenocorticotropin and lower levels of serum growth hormone, suggesting the presence of hypothalamic-pituitary stress. CONCLUSION: The prevalence of sleep disturbance has been increasing in long COVID patients infected in the Omicron phase with a certain clinical and endocrine trend.

Transitional Changes in Fatigue-Related Symptoms Due to Long COVID: A Single-Center Retrospective Observational Study in Japan.

Background and Objectives: Changes in post COVID-19 condition (PCC) characteristics caused by viral variants have yet to be clarified. We aimed to characterize the differences between clinical backgrounds and manifestations in long COVID patients who were infected with the Delta variant and those who were infected with the Omicron variants. Materials and Methods: This study was a single-center retrospective observational study for patients who visited our COVID-19 aftercare outpatient clinic (CAC) established in Okayama University Hospital (Japan) during the period from 15 February 2021 to 15 July 2022. We classified the onset of COVID-19 in the patients into three groups, the preceding, Delta-dominant, and Omicron-dominant periods, based on the prevalent periods of the variants in our prefecture. Results: In a total of 353 patients, after excluding 8 patients, 110, 130, and 113 patients were classified into the preceding, Delta-dominant, and Omicron-dominant periods, respectively. Patients infected in the Omicron-dominant period had significantly fewer hospitalizations, milder illnesses, more vaccinations and earlier visit to the CAC than did patients infected in the Delta-dominant period. Patients infected in the Omicron-dominant period had significantly lower frequencies of dysosmia (12% vs. 45%, ** p < 0.01), dysgeusia (14% vs. 40%, ** p < 0.01) and hair loss (7% vs. 28%, ** p < 0.01) but had higher frequencies of fatigue (65% vs. 50%, * p < 0.05), insomnia (26% vs. 13%, * p < 0.05) and cough (20% vs. 7%, ** p < 0.01) than did patients infected in the Delta-dominant period. Conclusions: The transitional changes in long COVID symptoms caused by the two variants were characterized.

Clinical Characteristics of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) Diagnosed in Patients with Long COVID.

Background and Objectives: COVID-19 can be serious not only in the acute phase but also after the acute phase and some patients develop ME/CFS. There have been few studies on patients with long COVID in whom ME/CFS was diagnosed by physicians based on standardized criteria after examinations and exclusion diagnosis and not based on only subjective symptoms. The purpose of this study was to elucidate the detailed characteristics of ME/CFS in patients with long COVID. Materials and Methods: A retrospective descriptive study was performed for patients who visited a COVID-19 aftercare clinic established in Okayama University Hospital during the period was from February 2021 to April 2022. Results: Clinical data were obtained from medical records for 281 patients, and 279 patients who met the definition of long COVID were included. The overall prevalence rate of ME/CFS diagnosed by three sets of ME/CFS criteria (Fukuda, Canadian and IOM criteria) was 16.8% (48.9% in male and 51.1% in females). The most frequent symptoms in ME/CFS patients were general fatigue and post-exertional malaise (89.4% of the patients), headache (34.0%), insomnia (23.4%), dysosmia (21.3%) and dysgeusia (19.1%). Dizziness, chest pain, insomnia and headache were characteristic symptoms related to ME/CFS. The male to female ratio in ME/CFS patients was equal in the present study, although ME/CFS was generally more common in women in previous studies. Given that patients with ME/CFS had more severe conditions in the acute phase of COVID-19, the severity of the acute infectious state might be involved in the pathophysiology of ME/CFS. Conclusions: The prevalence rate of ME/CFS and the characteristic sequelae in the long COVID condition were revealed in this study.

Application of Kampo Medicines for Treatment of General Fatigue Due to Long COVID.

Evidence regarding treatment for the acute phase of COVID-19 has been accumulating, but specific treatment for long COVID/post-COVID-19 condition has not yet been established. Treatment with herbal medicine might be one treatment option for long COVID, but there has been little research on the effectiveness of herbal medicine for long COVID. The aim of this study was to clarify the prescription patterns of Kampo medicines, which are herbal medicines that originated in China and were developed in Japan, for the treatment of general fatigue due to long COVID. A retrospective descriptive study was performed for patients who visited a COVID-19 aftercare clinic established in Okayama University Hospital during the period from Feb 2021 to Dec 2021 with a focus on symptoms accompanying general fatigue and prescriptions of Kampo medicine. Among the clinical data obtained from medical records of 195 patients, clinical data for 102 patients with general fatigue and accompanying symptoms were analyzed. The patients had various symptoms, and the most frequent symptoms accompanying general fatigue were dysosmia, dysgeusia, headache, insomnia, dyspnea, and hair loss. Prescriptions of Kampo medicine accounted for 24.1% of the total prescriptions (n = 609). The most frequently prescribed Kampo medicine was hochuekkito (71.6%) and other prescribed Kampo medicines were tokishakuyakusan, ryokeijutsukanto, juzentaihoto, hangekobokuto, kakkonto, ninjin'yoeito, goreisan, rikkunshito, and keishibukuryogan. Since the pathophysiology of general fatigue after an infectious disease is, in general, considered a qi deficiency in Kampo medicine, treatments with such compensation agents can be the major prescription as a complement for the qi. In conclusion, Kampo medicine can be one of the main pharmacological treatments for long COVID accompanying general fatigue.